1. Field of the Invention
The present invention relates generally to systems and methods for indexing, archiving, analyzing and reporting pipe and other void data, and more specifically, the present invention is directed to the multi-dimensional indexing and correlation of spatial, temporal, feature and context-based data in pipe and other void networks.
2. Description of the Background
In modern society, there are a great variety of existing and planned networks of pipes and other voids that are used for a wide variety of tasks. In most instances, these pipes degrade over time and are periodically inspected and/or repaired in order to extend the useful life of the pipes. In the present application, the term “pipe” or “pipeline network” will be used to represent all forms of voids and/or networks of voids characterized by at least partially hollow channels through which a robot or other inspection platform may travel. A convenient example used herein is a subterranean network of pipes used for sewers or potable water as is well known to those skilled in the art, but the present invention is not limited to such networks.
Current inspection platforms, for examining and cataloging the internal features of pipeline networks or other networks of voids, typically utilize sensors attached to a mobile base that is tethered to a remote control and data collection station at the surface (for subterranean networks). Sensing is primarily accomplished by imaging sensors such as cameras, lasers and sonar which collect data that is referenced to the tether payout length. This payout length is presumed to represent the current linear offset of the inspection device from the point of ingress into the pipe network. This method results in a pipe data model that utilizes discrete coordinate frames that are derived from data acquisition positions that are referenced to this payout or linear footage of ingress.
However, this is an insufficient model because pipe systems are not one-dimensional, straight networks. Rather, as represented by FIG. 1, pipe systems are typically large, complex networks with many interconnected segments and joints. As represented by the moving coordinate frame (CF) in FIG. 1, as each sensor onboard the inspection device traverses this network, linear footage cannot fully represent the sensor's path through the system as it passes by and through various branches and forks in the pipe. Specifically, as the sensor moves from position CF1 to position CF2 (at the junction of two pipes), the inspection device may travel in either of two directions (represented by CF3 and CF3, in FIG. 1).
Therefore, as shown in FIG. 1, when a sensor encounters a branch in the pipe, footage indexed data becomes ambiguous because points along two or more forward paths will share the same footage values. Specifically, the CF3 and CF3, positions would be characterized by the same payout length, and are therefore ambiguous. Clearly, as more complex pipe networks are explored, the ambiguity problem quickly multiplies and renders the collected data almost meaningless.
Similarly, traditional mobile inspection platforms for inspecting pipe and other void networks utilize a primitive system of fusion between data collected from different sensors. Traditionally, each sensor is sampled and recorded individually, resulting in one or more individual data streams which represent an inspection run. If more than one data stream is collected, the streams may be fused or logically cross-referenced at a data viewer, but there are no inherent links between the various collected data types.
In short, data from multiple sensors may be statically combined in real-time by combining the two streams into a single modified stream (as in the case of adding well-known “screenwriting”), or may be logically combined at a later time (as in the case of annotated image streams). In either case, it is difficult if not impossible to later extricate the “merged” data streams from one another. Moreover, dynamically adding or altering the data types stored in a stream, which is especially useful when analyzing multiple environmental sensors that are recording data on similar spatial locations, is impractical and not currently employed under these traditional systems.
Since there is no way to cross-reference these resultant data streams aside from logical relationships, it is difficult to analyze disparate data streams. In practice, multiple inspection runs with imaging sensors are typically compared qualitatively using feature identification and matching, either by a human or autonomous agent. However, in employing this methodology, a large amount of information about pipe condition is lost due to the insufficient precision of these qualitative comparisons. It has therefore typically been deemed necessary to fuse individual data streams during inspection to better extract information from many individual collection runs and/or many different sensors.
Error modeling is also not addressed by this current data collection model. Each sensor has limits in accuracy that will accumulate and affect other sensor data when multiple data streams from different sensors are fused together. For example, stretch in cables (e.g., payout tethers) can distort measurements of distance, and inaccuracy in position can cause deviations in the expected perspective of imaging equipment. This information is critical in estimating the accuracy of any quantitative data analyses that utilize these sensors, and must be included with the sensor data.
Thus, traditional systems and methods for collecting and analyzing pipe inspection data do not adequately correlate disparate data sets and do not address error modeling. By correlating and indexing various pipe data, the present invention provides more thorough and more reliable data analysis and even provides new types of analysis not heretofore possible. Moreover, the present systems and methodologies are applicable to a wide variety of voids other than the subterranean pipeline networks described herein. For example, the present devices and methodologies could be used with pipes, caves, tunnels, tanks, pipelines, conduits, trenches, subterranean voids, and/or wells, among others.